Location control of a mobile robot based on fuzzy PID and adaptive filtering LMS and RLS (LACCEI, 2024)
The development of traditional PID control systems requires mathematics to find the optimal tuning constants. In contrast, fuzzy controllers are simpler to use because their implementation is based on inference rules created by an expert. In this work, a PID fuzzy controller and an adaptive filter have been implemented in a children healthy treatment mobile robot prototype to control its position, evaluating different membership functions and the behavior of the adaptive filter against external disturbances. Simulink and Arduino have been used for this purpose by means of serial communication. The robot prototype has been designed using inventor, printed with 3D technology. The most efficient controller has been the PD controller, reaching a stability not achieved by the other controllers. The PD controller has been complemented with an adaptive RLS filter, which in turn was the one that obtained the minimum error compared to the LMS filter.